Optimal Allocation in Enterprise Human Resource Management through Intelligent Scheduling Algorithms
DOI:
https://doi.org/10.13052/jicts2245-800X.1422Keywords:
intelligent scheduling, human resource management, genetic algorithm, co-evolutionAbstract
The paper provides a brief introduction to the mathematical model of project scheduling optimization and the genetic algorithm (GA) used to optimize the human resource allocation scheme. The GA was improved by co-evolution and adaptive genetic parameters. Subsequently, simulation experiments were conducted, and the improved algorithm was also compared with the particle swarm optimization (PSO) algorithm and traditional GA. The results demonstrated that the improved GA converged to stability more quickly during the search for the optimal solution, resulting in a more excellent objective function upon convergence. Overall, the scheme optimized by the improved GA exhibited lower human resource costs and a shorter completion cycle.
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